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Robustná kanonická korelačná analýza (Robust CCA)×Kanonická korelačná analýza×
OdborŠtatistikaŠtatistika
RodinaLatent structureLatent structure
Rok vzniku20031936
TvorcaCroux & Dehon (building on Hotelling's CCA framework)Harold Hotelling
TypRobust multivariate associationMultivariate linear dimension reduction and association
Pôvodný zdrojCroux, C. & Dehon, C. (2003). Robust estimation of the canonical correlations. Computational Statistics, 18(3), 555–569. link ↗Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28(3–4), 321–377. DOI ↗
Ďalšie názvyRobust CCA, RCCA, robust CCA, outlier-resistant canonical correlationCCA, canonical variate analysis, canonical analysis, multiple canonical correlation
Príbuzné44
ZhrnutieRobust canonical correlation analysis extends classical CCA by replacing the standard sample covariance matrix with a robust estimator — such as the Minimum Covariance Determinant (MCD) or S-estimator — so that outlying observations do not distort the estimated canonical correlations and canonical variates between two sets of variables.Canonical Correlation Analysis (CCA) is a multivariate statistical method that identifies pairs of linear combinations — one from each of two variable sets — such that the correlation between each pair is maximised. Introduced by Harold Hotelling in his landmark 1936 Biometrika paper, CCA provides the most general linear framework for studying the association between two multivariate batteries of measurements, and many classical procedures (multiple regression, MANOVA, discriminant analysis) are special cases of it.
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ScholarGatePorovnať metódy: Robust Canonical Correlation Analysis · Canonical Correlation Analysis. Získané 2026-06-18 z https://scholargate.app/sk/compare